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SEONT: Semantics & mapping exercise to add structure to messy socio-economic data

Year: 2020
Format: MP4
Language: English
Publisher: CGIAR Platform for Big Data in Agriculture
Alternative Title: Webinar- SEONT, the Socio-Economic Ontology
Type: Video
Place of Publication: France
Tags: Webinar
Keywords: Socioeconomic Data
Keywords: Standardization
Keywords: Big Data
Description: This session is the fifth webinar of the series: All about our products and their uses, organised by the Ontologies Community of Practice. During this webinar, Gideon Kruseman and Soohno Kim guide us in the conception, development and content of SEONT, the Socio-Economic Ontology built by the CGIAR and partners to annotate agricultural household surveys. Xingyi Song presents the machine learning tool, based on natural language processing, developed by the University of Sheffield to extract SEONT terms from 100 core socio-economic questions. Finally, Berta Miro closes the webinar by unfolding a story about annotating CGIAR survey data using SEONT and other ontologies via the machine learning tool developed by the University of Sheffield.
Personages: Céline Aubert
Personages: Gideon Kruseman
Personages: Soohno Kim
Personages: Xingyi Song
Personages: Berta Miro
Personages: Elizabeth Arnaud
Agrovoc: DATA
Agrovoc: SURVEYS
Access Rights: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International § CIMMYT manages Intellectual Assets as International Public Goods. In case you want to make non-exclusive commercial use of this item or you want to adapt it in any manner and use such adaptation, please contact indicating the code/name of this item and the kind of use you intend; CIMMYT will contact you with the terms and conditions for such use.
Notes: Video also available in YouTube:
Corporative Creator: CGIAR Platform for Big Data in Agriculture
Duration: 1:15:03

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